Biomarkers are surrogate measures of specific changes in biological processes, such as increases or decreases in blood proteins or other analytes, that relate to changes in disease state, or changes in response to drug treatment, environmental components, food, nutrients, etc,. For example, biomarkers as surrogate clinical measures detect early biological responses after drug treatment for analyzing drug safety and early efficacy in testing new drugs. Biomarkers have both prognostic and diagnostic uses. For instance, once the disease status is established, these markers can be used to predict the likely course of the disease and to monitor and assist in the management of disease. One can use biomarkers to stratify diseased populations. Lastly, screening large populations with biomarkers leads to the discrimination of a healthy state from early asymptomatic stages of the disease. Thus, biomarkers can be used for disease management, through diagnosis, staging, stratification and measures of progression and prognosis, and, most importantly, for early measures and/or predictors of drug efficacy or toxicity.
The pharmaceutical industry is interested in biomarker discovery for two main reasons. First, the increasing rate of drug candidate attrition has reached levels where the cost effectiveness of drug discovery and development becomes questionable. The root causes of drug candidate attrition have been identified as resulting from a poor understanding of the mechanism of action of the candidate and from poor pharmacological validation and translation of cellular and animal model-based results to the clinic. The use of biomarkers can bridge the gap between cellular and animal models and human clinical conditions, and new biomarkers, such as HER2, are likely to be relevant to drug mechanisms of action as predictors of drug efficacy. Another major cause of attrition is the individuality of drug toxicity reactions. Identification of individuals with idiosyncratic and other unexpected responses will save lives and money and will allow the introduction of safer drugs. Examples of efficient genetic biomarkers of this type have been reported recently.
Secondly, the high cost of clinical trials for candidate drugs for slowly progressing chronic diseases is prohibitive. Chronic diseases such as Alzheimer disease, type II diabetes, cancer, cardiovascular diseases, rheumatoid arthritis, osteoarthritis and chronic obstructive pulmonary disease represent a major fraction of health care costs and contribute significantly to the direct cause of death. The size of the market and the needs of the public are tremendous in these disease areas, which beg for effective mechanism-based drugs. Yet, the slow, progressive nature of these diseases poses a currently insurmountable problem. The minimal measurable improvement (20-30%) in disease symptoms occurs over such a long period of time that it is impractical and too expensive to test potential therapies in clinical trial settings. The expectation for disease progression-specific biomarkers is that they will permit the prediction of improvement earlier than such improvement actually occurs, thus providing a useful tool to measure and predict the efficacy of novel candidate drugs in shorter and less expensive clinical trials.